A Machine Learning way to Build Trust on Social Network.
ChitralaKavitha1, S. Nageswararao2
1*ChitralaKavitha, CSE, Vardhaman College of Engineering, Affiliated with Jawaharlal Nehru Technological University, Hyderabad, India.
2NageswararaoSirisala, CSE, Vardhaman College of Engineering, Affiliated with Jawaharlal Nehru Technological University, Hyderabad, India.
Manuscript received on November 24, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 5202-5207 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4259129219/2019©BEIESP | DOI: 10.35940/ijeat.B4259.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A social network is a type of service provided by the online platform where an individual can communicate easily with each other, it also provides personal relationships and social interactions. Apart from this it also provides the website where users can build a public figure(profile) and can interact with other users. The social networking sites mainly have the trust issues to overcome, this we tried to build trust in online networks by using the Naive Bayes algorithm algorithm which is deployed through by communication direct and indirect trust and for calculating the trust values Bayesian conditional and Dempster-Shafer theory is implemented. Reenactment results with various arrange parameters are introduced to show the adequacy of the proposed plan.
Keywords: Online social network, Trust, Indirect trust, Naïve Bayes.